Integrating plans and strengthening communications through artificial intelligence and machine learning

Deepa Srinivasan
Vision Planning and Consulting, LLC, USA

Andrew R. Estrain
Vision Planning and Consulting, LLC, USA

Plan integration is currently performed manually and it is met with several challenges, obstacles, and inconsistencies, and the current way is often ineffective. The problem that arises is that hazard mitigation is often forgotten about during other community planning initiatives, resulting in a lack of integration of hazard mitigation and risk reduction principles into other important planning initiatives. This research project aims to reduce these problems by employing Artificial Intelligence (AI) and Machine Learning (ML) for the automated integrated planning of hazard mitigation principles. Our team built an automated AI application that utilizes the concept of ML to reduce the current challenges associated with manually performing plan integration, and to provide an automated platform to for communities to integrate hazard mitigation principles into other community planning initiatives and documents. Application development is completed through a two-phase process: Phase 1: Build the Brain and Phase 2: Process the Plans. Ultimately, this project strengthens the resilience of policy and governance infrastructure by providing a central online location to view potential gaps in planning initiatives, for intergovernmental coordination and for identifying recommendations to fill gaps and challenges. The end product is a new automated AI application that will help align existing plans, goals, visions, policies, actions and help increase hazard mitigation and coordination and communications during hazard events.